Hi all,
and a happy new year. I hope everyone feels Y2K-compliant. We would like to
ask
for guidance about some aspects of affine (linear) normalization.
We are in the middle of analyzing a sizable number of structural MRIs which
we
have segmented (using a combination of spm-based and other routines) and
normalized using spm99b. During the normalization they have been resampled
from
0.975x0.975x1.5mm voxel size to 1mm isotropic. Normalization was by
12-parameter
affine and the default (7x6x7 basis functions etc.) nonlinear procedure.
What we
want to do now is to apply masks in Talairach space to the normalized data,
do
some kind of voxel-counting inside those masks, and then calculate the
volume in
original space corresponding to the number of voxels counted in the
normalized
data.
Our reasoning has been as follows:
1) Since the nonlinear part of the normalization cannot be easily (or at
all?)
inverted, we want to redo the normalization using just the affine part,
using
the _sn3d.mat files generated before (i.e. with the nonlinear part switched
on)
Question: From my understanding of the algorithm, the affine transformation
contained in these files should be the same as the one that would have been
generated if the nonlinear part of the normalization had been switched off.
Correct?
Question: If that is correct, we'd like to save computational overhead by
using
the affine
matrix that we already have. Is there a way to modify the _sn3d.mat files so
that only the linear normalization is applied?
2) From affine geometry, we would expect that the (absolute of the)
determinant
of the affine transformation matrix gives the volume change under the
transform.
Correct? So we should be able to divide the total volume of the voxels
counted
in normalized space by this number to get the corresponding volume in the
original space.
In trying to verify this, we have run into the following problem: The affine
transformation matrix that is printed by the normalization routine looks
nothing
like the matrix contained in the variable 'Affine' in _sn3d.mat. For
example:
I. In the Spatial Normalization display and print out:
Linear (Affine) Component - no flipping
X1 = 1.201*X - 0.137*Y - 0.073*Z + 1.270
Y1 = 0.165*X + 1.051*Y + 0.444*Z + 1.284
Z1 = 0.004*X - 0.514*Y + 1.113*Z - 2.366
II. By loading the masked_T1_sn3d.mat file:
The Affine matrix is:
[ 1.0896 0.1478 0.0120 4.1977
-0.2264 1.6664 -0.6800 65.1923
-0.1106 0.7691 1.6016 8.0781
0 0 0 1.0000 ]
Apparently they are stored in different formats. Could you explain what
these
are and which we should use for the intended purpose?
Thanks for your help, kind regards, Andreas
Andreas Meyer-Lindenberg, MD PhD (Dr. med. Dr. med. habil.)
Research Fellow
Unit on Integrative Neuroimaging, Clinical Brain Disorders Branch,
National Institute of Mental Health, NIH
10-4C101, 9000 Rockville Pike
Bethesda, MD 20892-1365
(W) (301) 496 9672 (F) (301) 496 7437 email [log in to unmask]
